Automated color control in film-to-digital transfer

ABSTRACT

A system and method for automatically adjusting color parameters during a film-to-digital transfer. An operator uses standard telecine equipment to preview scenes in order to determine a natural clustering of fields or scenes. Each cluster is processed separately. All the fields in a cluster are treated as one unit in the sense that color adjustments for the cluster are based on the cluster color histogram, which is computed by aggregating the colors from all pixels in the cluster. Constraints are specified for the cluster. Variables of a constraint may be automatically specified or determined by an operator based on observing sample frames from the cluster. In addition, the operator can nullify a constraint if desired. Within each cluster, the system adjusts red, green and blue intensities of the digitizing device, gains for each of these color channels, and other parameters. The system first determines which settings respect the constraints and then optimizes the solution. The solution is optimized such that the digital color distribution is as faithful as possible to the film color distribution subject to the constraints. This is achieved by adjusting the settings to maximize the entropy of the empirical, digital color histogram among all settings respecting the constraints.

PRIORITY

[0001] The present application claims priority from U.S. ProvisionalPatent Application No. 60/285,561 filed on Apr. 20, 2001, entitled“Automated Color Control in Film-to-Digital Transfer” having Atty.Docket No. 1748/113 which is incorporated by reference herein in itsentirety.

BACKGROUND OF THE INVENTION

[0002] Film is commonly digitized and transferred either to digital tapeor to a computer disk. Once the film is placed in digital form it mayundergo additional processing such as color correction, standardsconversions, nonlinear editing, “panning and scanning,” compression,and/or various forms of digital filtering.

[0003] In the process of correcting the color, the distribution ofcolors in the film representation are balanced against the visualappearance that the colors have when displayed on a display device. Someof the desired attributes take into account perceptual properties of thehuman visual system. Certain relationships among color components mustbe preserved so that, for example, “blacks appear black,” “whites appearwhite” and color tinted flesh tones appear natural. The correspondingrelationships between color distributions and display devices arewell-known to experts. For example, it is known how red, green and blueshould be mixed in order to look “black” on a given monitor, or to havethe appearance of flesh.

[0004] The transfer from film to digital format is controllable throughvarious settings on a digitization device which affect the intensitiesand other properties of the color components. The settings control for“lift”, “gamma,” “gain” and other standard parameters, are implementeddigitally from what is recorded to what is output. Some digitizationdevices allow for the control of the exposure time of each colorchannel, thereby effectively adjusting the three intensities. Althoughthe details may differ from one device to another (corresponding to adifferent way of imaging the film), the effects of adjusting theparameters can be observed both mathematically by examining the colorhistogram and visually by watching the video on standard monitors. Inall current systems, an operator supervises the transfer, determines theproper settings for the variables, and is ready to make adjustments asmay be needed because of changing characteristics of the material. Inparticular, current systems are not automated.

SUMMARY OF THE INVENTION

[0005] A system for automatically adjusting intensity, gain and othercolor parameters during a film-to-digital transfer is disclosed. Thesystem can operate in a range of modes from fully automatic to fullyinteractive. The system collects statistics on the distribution of colorintensities in digitized film/video and automatically computesadjustments to the color intensity, gain and other settings in orderthat the visual appearance of the digital representation accommodatesstandard constraints on colors and color relationships. Theseconstraints may be determined automatically or in conjunction with anoperator. Among these constraints are that “blacks appear black” and“whites appear white,” that “clipping” and “banding” are limited, andthat there is proper “color balance.” It should be understood that manyother constraints may be defined for an image or a cluster (group ofimages) and that the constraints which are mentioned are only exemplary.A method for specifying and determining the optimal control settingsubject to the assembled constraints, namely the overall control settingwhich maximizes the information content of the observed colordistribution is also disclosed.

[0006] An operator uses standard telecine equipment to preview scenes inorder to determine a natural clustering of fields or scenes. Eachcluster is processed separately. All the fields in a cluster are treatedas one unit in the sense that color adjustments for the cluster arebased on the cluster color histogram, which is computed by aggregatingthe colors from all pixels in the cluster. Constraints are specified forthe cluster variables of a constraint may be automatically specified ordetermined by an operator based on observing sample frames from thecluster. In addition, the operator can nullify a constraint if desired.Within each cluster, the system adjusts red, green and blue intensitiesof the digitizing device, gains for each of these color channels, andother parameters. The system first determines which settings respect theconstraints and then optimizes the solution. The solution is optimizedsuch that the digital color distribution is as faithful as possible tothe film color distribution subject to the constraints. This is achievedby adjusting the settings to maximize the entropy of the empirical,digital color histogram among all settings respecting the constraints.

[0007] Once the settings for a given cluster are determined, thefilm-to-digital transfer begins. The results of the ongoing transfer aretracked, checking that the current settings are adequate to continue toachieve good color balance, good contrast and good dynamic range.Settings are adjusted, scene by scene, as needed.

BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The foregoing features of the invention will be more readilyunderstood by reference to the following detailed description, takenwith reference to the accompanying drawings, in which:

[0009]FIG. 1 is a block diagram showing an exemplary system forautomating color correction functions;

[0010]FIG. 2A is a spatial representation showing all allowable controlsettings which is designated as the control space and a subset ofsettings labeled allowed settings which meet constraint criteria;

[0011]FIG. 3A shows a color histogram for film data which has beentransferred to digital form but has not been color corrected;

[0012]FIG. 3B shows a color histogram for digital video which has beencolor corrected by a set of control settings which meets all constraintsbut is non optimal;

[0013]FIG. 3C shows a color histogram for digital video which has beencolor corrected by a set of control settings which meets all constraintsand is an optimal solution exhibiting maximum entropy;

[0014]FIG. 4 is a flow chart of the steps for color control in film todigital video transfers; and

[0015]FIG. 5 is a flow chart of the steps for color control in analternative embodiment.

DETAILED DESCRIPTION

[0016] It should be understood by one of ordinary skill in the art thatfilm is composed of frames which are whole images while digital video isgenerally composed of fields which are one half of a whole film image.Video fields are either designated as odd or even corresponding to thelines of an image frame which are represented by the field. Digitalvideo may also be composed of frames representing a whole image from afilm frame. The term “frame” as used herein shall apply to both completeimages and also to interlaced image fields. The term “cluster” as usedherein refers to one or more frames (film/video). Generally a cluster isa group of frames which compose a scene or a group of scenes from afilm. Clusters can be designated by an operator or may be automaticallydetermined. The term “color information” shall refer to the digital datathat is associated with color. For example R,G,B values for a pixel,field, frame or cluster. The term “color parameter” includes but is notlimited to hue, saturation, and brightness. The term “control setting”as used herein refers to an arrangement of one or more color controlswherein each control sets a particular color parameter. A controlsetting causes color information from one or more film frames to bealtered. For example, a control setting may include a brightness level,a hue level, and a saturation level and will alter the R,G,B colorinformation.

[0017] It should be understood by one of ordinary skill in the art thatcolor may be represented in any of a number of color spaces such asMunsell, Ostwald, CIE, RGB, and YUV for example and the invention asdisclosed is not limited to any particular color space. Throughout thisdisclosure it is assumed that the intended display mechanism for thedigital video is fixed such that any variations between displays is nolonger a variable.

[0018] A system for color correction during a film-to-digital transferis shown in FIG. 1. The system includes a digitization device 10 forreceiving as input film frames 12 and outputting a digital videosequence 14 composed of video fields or frames 13. The digitizationdevice 10 samples the film and quantizes the color samples. In otherembodiments, the digitization device receives a digital sample of thefilm and provides a mechanism for color correction. The digitizationdevice is provided with adjustable controls 15 for changing colorparameters 16 which adjusts the color information 17 in the digitalrepresentation and as a result the visual appearance in any particulardisplay mechanism. For example, each color may have an associatedcontrol 15 for independent adjustment, such that in an R,G,B color spaceall of the red values may be increased or decreased. Similarly controlsmay alter groups of colors such that the hue, saturation or brightnessmay be changed. For example, the brightness at high intensities can beadjusted to prevent “ballooning” and to get “soft clipping,” whereasbrightness at low intensities can be adjusted to get sufficient detailin the dark areas of an image or a cluster. Each possible controlsetting of these controls leads to a different color distribution of thecolor information for a cluster of frames.

[0019] A processor 20 executing software 25 interacts with thedigitization device for adjusting the color parameters 16 for a controlsetting 15 of the digitization device for the video transfer. Althoughthe following description shall refer to software, it should beunderstood by one of ordinary skill in the art that the software may beembodied on an integrated circuit or may be a combination of computercode and hardware. The software can be set to adjust the colors of acluster of film frames either automatically or semi-automatically withinput from a human operator. The software insures that conventionalrequirements on the distribution of color information within eachcluster of video frames are satisfied while at the same time preservinginformation from the original distribution of colors.

[0020] The problem of color correction is formulated in the context ofconstrained optimization. The conventional requirements on thedistribution of colors will be referred to as “constraints”. Theconstraints are dependent on the display mechanism for the digital videorepresentation. Typical examples of constraints are “blacks should lookblack,” “whites should appear white,” and the overall average of thecolor channels should be “gray.” A further constraint is that human skinshould look like flesh. Other possible constraints are that there shouldbe limited “banding” and “clipping” in the dark and light areas of avideo image when it is displayed on a display device. Some constraintsare most naturally addressed in the RGB color space, whereas otherconstraints may be better addressed in other color spaces. The softwareis therefore provided with the ability to change between color spaces.For example, some of the color fidelity issues referred to below aregenerally address in “C_(b)/C_(r) color space”, referring to a colorcoordinate system based on a luminance or intensity variable Y=ρR+γG+βBwhere R, G, B stand for red, green and blue, and ρ, γ, β, are positiveparameters with ρ+γ+β=1. The other two components in this representationare C_(b)=Y−B and C_(y)=Y−R. Thus C_(b)/C_(r) space is simply a lineartransformation of R, G, B-space.

[0021]FIG. 2A shows a 2-D control space along with possible controlsettings within the control space wherein each control setting isindicated with a Θ. Each constraint may be represented as a property ofan empirical three-dimensional histogram of colors related to thetotality of pixels in the corresponding sequence, which constitutes thecluster. Some control settings yield a histogram which comply with theconstraints, and some do not. The control settings which are within thespace of all constraints are represented with a Θ* while the optimumsetting is marked with a Θ**. The method for determining Θ** will beexplained below. FIG. 3A shows a representative 2-dimensional version ofthe 3-D histogram wherein only one color component is represented, whichin this example is the color component red. This histogram representsthe sampled color information from a cluster of frames prior to beingaltered by changes in the control settings of the digitization device.

[0022] FIGS. 3B-3C show altered 2-D color histograms of the histogramdisplayed in FIG. 3A. FIG. 3B shows a histogram wherein the controlsettings are changed thereby altering the histogram. The settings usedto produce the color information of FIG. 3B comply with all of theconstraints and therefore would reside within the shaded portion of thecolor space representation of FIG. 2A. FIG. 3C is also a histogram whichcontains altered color information which complies with all of theconstraints and represents the optimal solution Θ** from FIG. 2A.

[0023] Among the settings that respect the constraints, a method isdefined for ordering the solutions and therefore finding an optimalsetting in the sense of sharing as much information as possible with thedistribution of colors in the film representation. FIG. 4 is a flowchart showing the steps used to determine such a control setting. Firsta set of constraints are determined (Step 401). Each constraint is afunction which depends upon the color information. The constraints aredefined by one or more variables which may be either set by an operatoror automatically set within the constraint function. If the variablesare automatically set this step may be bypassed. The constraints as wellas the extent of automation of the constraints may be cluster-dependent.

[0024] A first constraint is color fidelity. Black regions in theoriginal film representation should also look black (when the digitalmaterial is displayed), white regions should look white, flesh tonesshould appear natural. All of these constraints are based upon humanperception. The corresponding quantitative constraint on the colordistribution can be determined either automatically, for instance byidentifying peaks near actual black (in a 3D color histogram of thecolor information) and requiring that the colors of the correspondingpixels be black, or with the assistance of an operator 5 manuallyspecifying a spatial region in one or more frames in the cluster thatneeds to look black. In the purely automated case, a constraint might bethat a certain percentage of pixels for a cluster must be at full black(R,G,B,=0,0,0), for instance 10% of all pixels.

[0025] In another variation which includes operator input, an operatorcould adjust the percentage variable for the constraint.

[0026] The second constraint is balance, such that the overall mean ofthe empirical color distribution of the color information associatedwith the cluster should be gray. This implies that the average color ofall the pixels in the cluster should lie on the diagonal (R=G=B) in thethree-dimensional color space. In an automated version the particularlevel of gray would be automatically chosen. In a semi-automatic mode ofoperation, the particular level of grey might be specified by theoperator.

[0027] Avoidance of clipping is another constraint. Clipping occurs whena large number of pixels, usually very dark or very light, are assignedthe same quantization level in the color histogram. This results fromthe quantization problem wherein shades between two colors must beassociated with one of the two colors. Clipping is detected by searchingfor certain peaks in the histogram which are indicative of clipping.Such peaks normally occur at high or low light intensity levels andappear as a line on the histogram. Such lines in the histogram usuallyindicate that too much detail has been lost in the quantization processfrom the high resolution of film to the lower resolution of digitalvideo. The software can search for the slope of the line between pixelpoints having high or low light intensity levels to determine ifclipping is occurring. One method of implementing the constraint is toidentify a minimum slope in a set number of directions from a pixel forcompliance.

[0028] Another constraint is the noise level of the color information.Noise occurs when similar exposure values from the film get mapped tovery different color information values. Like the banding problem, noiseis reflected in the shape of the color histogram, in this case, by gapsin the dark areas which indicate that similar values on the film havebeen mapped by the settings to very different values in the video realm.The corresponding constraint refers to the absence of such gaps. Theconstraint may be defined by a difference measurement in color betweenneighboring groups of pixels, such that if the difference measurementexceeds a threshold the constraint is complied with.

[0029] Clipping, banding and noise are relatively more objectionable indark regions than in bright ones because the eye is more sensitive todetail in dark areas. Therefore, the constraints may be defined to bemore sensitive for a certain black level. Taking into account one ormore of such phenomena leads finally to a series of constraints on thecolor histogram.

[0030] A digitized version of each film frame is either created throughan A/D conversion in a digitization device or a digitized version isimported which includes the color information (Step 402). The digitalfilm is then segmented into clusters which may contain one or moreframes (Step 403). The cluster may be manually selected by a humanoperator of the digitization device or the cluster may be automaticallycreated based upon characteristics of the digital information as isknown to one of ordinary skill in the art. In other embodiments, thefilm frames may be divided into clusters prior to conversion to thedigital domain. Further, it should be understood that the constraintsmay be defined after the clusters are determined and in some embodimentsin which the constraints are cluster dependent this is the preferredsequence of steps.

[0031] A cluster is then selected for processing (Step 404). Controls ofthe digitization device are then automatically set to a first setting ofa plurality of possible settings which alters the color information forthe cluster (Step 405). It should be understood by one of ordinary skillin the art that the changes to the control settings may be done within aprocessor which is located within the digitization device. Further, itshould be understood that the number of control settings cannot be aninfinite number for a practical implementation. As a result, the controlspace having control settings must be limited to a finite number ofvalues. For instance, gain may have a scale from 0-1.0 which potentiallyhas an infinite number of levels however the parameter may be defined in0.001 increments such that there are 1000 finite levels. Similarly, thiswould hold true for all color parameters that make up a single controlsetting.

[0032] The adjusted color information is then analyzed to see if itcomplies with all of the constraints (Step 406). If the colorinformation of the control setting does comply with all of theconstraints then the control setting is saved (Step 407). If the colorinformation does not comply with all of the constraints the controlsetting is discarded (Step 408) This process is continued iterativelyuntil all of the possible settings which comply with the constraints areidentified (Step 409).

[0033] More specifically, let F₁,F₂ . . . F_(N) denote the video framescorresponding to a cluster, and consider a standard red, green, bluecolor representation so that F_(n)=(F_(n,r,)F_(n,g,)F_(n,b)), where inturn each of the three components is a mapping from a lattice of pixelsl to a range of intensity values, for example {0,1, . . . , 255} (“8 bitquantization”) or {0,1, . . . , 1023} (“10 bit quantization”). Supposethe lattice f is of dimension L×W. and let hist (r, g, b) represent thecolor histogram derived from the cluster. The histogram is based onN×L×W color samples and defined, for each color point (r, g, b) in {0,1. . . 2^(B)−1}³, where B is the number of bits in each color channel, asfollows:

hist(r,g,b)=(NLW)⁻¹#{(n,x,y)∈{1,2, . . . ,N}×l:F _(n)(x,y)=(r,g,b)}

[0034] wherein #{A} indicates the number of elements in the set A.

[0035] Let Θ represent the possible range of settings on thedigitization device. Thus each θ∈Θ corresponds to one control setting.Each such setting θ then determines a potentially different histogram.The dependence on θ will be denoted by writing hist(r,g,b;θ). Theconstraints determine a subset of settings, namely those for whichhist(r,g,b;θ) displays the desired properties. Let Θ_(C)⊂Θ denote thecollection of control settings which comply with the constraints.

[0036] A score is then calculated for the control setting. (Step 410)The score is determined based upon the Shannon entropy of the colorinformation. The entropy provides the mutual information between thedistribution of color in the and the digital representations subject tothe constraints. This is true since each control setting may be regardedas a perturbation or quantization of the possible values of the filmcolor, and hence as a function Y=g(X) where the random variable Xrepresents the original color information at a randomly chosen pixel.The distribution of X is dependent on the film content and afterquantization the number of possible values is reduced to a finitenumber. The maximization of the mutual information between X and Y is aquantization of original color values which produces a video colorhistogram sharing as much information as possible with the distributionof colors in the film representation. The optimal control setting isequivalent to the setting which maximizes the entropy of Y among allallowable control settings. This can be shown by:

[0037] I(X,Y)=H(Y)−H(Y|X) where H(Y|X) is the conditional entropy of Ygiven X. Since Y is a function of X, the conditional entropy of Y givenX is zero i.e. H(Y|X)=0. Consequently, maximizing the mutual informationover all functions g is the same as maximizing the entropy H(g(X)) overall g. The entropy of g(X) depends only on the statistical distributionof g(X), which in turn depends only on the particular function (controlsetting) g since the distribution of X is fixed and needn't beexplicitly considered.

[0038] For each θ∈Θ, the entropy of hist(r,g,b;θ) is${H(\theta)} = {- {\sum\limits_{r,g,b}{{{hist}\left( {r,g,{b;\theta}} \right)}\log \quad {{hist}\left( {r,g,{b;\theta}} \right)}}}}$

[0039] where the sum runs all 2^(3B) allowable (r,g,b) values and logrepresents log base 2.

[0040] The process repeats until all of the settings complying with theconstraints have assigned scores based upon the entropy of the colorinformation for the cluster. An optimal setting is then determined.Optimality is determined based upon the control setting with the highestscore. The optimal setting is defined to be the one setting whichsatisfies the constraints which maximizes the Shannon entropy. Theoptimal θ* is then defined by$\theta^{\quad*} = {\underset{\theta \in \Theta_{C}}{\arg \quad \max}\quad {{H(\theta)}.}}$

[0041] The corresponding histogram hist(r,g,b;θ*) then represents thedigital representation which best matches the film representationsubject to the constraints.

[0042] The setting which provides the optimal score is preferablyselected, although any setting, may be chosen which satisfies all of theconstraints (Step 411). This process continues until a control settingis chosen for all of the clusters (Step 412). Preferably the optimalcontrol setting is selected for all clusters, although control settingswhich comply with all of the constraints may also be selected. To findthe optimal control setting, optimization techniques which are known inthe art may be employed, such as global optimization. When certainconstraints do not provide a linear mapping, other optimizationtechniques, such as, gradient methods or sub-optimal solutions, such asmaximizing the score over a subset of control settings may be employed.It should be understood by one of ordinary skill in the art that widevariety of optimization techniques may be employed depending on theconstraint functions. The method thus adjusts the settings in order tomaximize the entropy of the color histogram, but confining the searchover settings to those which implement the constraints.

[0043] In another embodiment as shown in FIG. 5, the method fordetermining the optimal control setting is determined by firstiteratively processing control settings until a control setting is foundwhich meets all of the constraints (Step 501). Next, the entropy of thatcontrol setting is determined as expressed above (Step 502). Another setof control settings, proximate to the original set of control settingsin the control space is then selected (Step 503). The entropy iscalculated for the proximate settings. (Step 504). The entropy valuesare then compared. (Step 505). The control setting with the greaterentropy is selected and saved. (Step 506). The process repeats to Step503 wherein another proximate control setting is selected from thecontrol space. This process iteratively continues until the controlsetting in the control space which exhibits the maximum entropy is found(Step 507). Computer code for searching for a maximum value is wellknown in the art and may be accomplished using many well knowntechniques.

[0044] In an alternative embodiment, the disclosed apparatus and methodfor automated color control may be implemented as a computer programproduct for use with a computer system including digitization devices.Such implementation may include a series of computer instructions fixedeither on a tangible medium, such as a computer readable medium (e.g., adiskette, CD-ROM, ROM, or fixed disk) or transmittable to a computersystem, via a modem or other interface device, such as a communicationsadapter connected to a network over a medium. The medium may be either atangible medium (e.g., optical or analog communications lines) or amedium implemented with wireless techniques (e.g., microwave, infraredor other transmission techniques). The series of computer instructionsembodies all or part of the functionality previously described hereinwith respect to the system. Those skilled in the art should appreciatethat such computer instructions can be written in a number ofprogramming languages for use with many computer architectures oroperating systems. Furthermore, such instructions may be stored in anymemory device, such as semiconductor, magnetic, optical or other memorydevices, and may be transmitted using any communications technology,such as optical, infrared, microwave, or other transmissiontechnologies. It is expected that such a computer program product may bedistributed as a removable medium with accompanying printed orelectronic documentation (e.g., shrink wrapped software), preloaded witha computer system (e.g., on system ROM or fixed disk), or distributedfrom a server or electronic bulletin board over the network (e.g., theInternet or World Wide Web). Of course, some embodiments of theinvention may be implemented as a combination of both software (e.g., acomputer program product) and hardware. Still other embodiments of theinvention are implemented as entirely hardware, or entirely software(e.g., a computer program product).

[0045] Although various exemplary embodiments of the invention have beendisclosed, it should be apparent to those skilled in the art thatvarious changes and modifications can be made which will achieve some ofthe advantages of the invention without departing from the true scope ofthe invention. These and other obvious modifications are intended to becovered by the appended claims.

We claim:
 1. A method for automated color control in converting film todigital video, the method comprising: receiving a series of digitalvideo frames having color information; determining a set of colorsettings producing altered color information which comply with one ormore color constraints; determining an entropy for each color settingwhich produces altered color information which complies with the one ormore color constraints; and selecting a color setting based upon theentropy.
 2. The method according to claim 1, further comprising:partitioning the frames into a plurality of clusters, wherein eachcluster includes at least one frame and each cluster has associatedcolor information; selecting a cluster; and determining a color settingfor each cluster.
 3. The method according to claim 1, wherein theselected color setting has the maximum entropy of the set of colorsettings.
 4. The method according to claim wherein the maximum entropycorresponds to the maximized mutual information between the colorinformation and the altered color information.
 5. A method for automatedcolor control in converting film to digital video, the methodcomprising: receiving a digital video stream composed of a plurality ofvideo frames; partitioning the frames into a plurality of clusters,wherein each cluster includes at least one frame and each cluster has anassociated color distribution; automatically determining at least onemodified color distribution for each cluster of digital video whichcomplies with one or more color constraints.
 6. The method according toclaim 5 further comprising iteritively processing possible colordistributions to identify any distributions which comply with all of theconstraints.
 7. The method according to claim 6 further comprising:grading the color distributions according to entropy.
 8. The methodaccording to claim 7 further comprising: selecting the colordistribution which has the maximum entropy.
 9. The method of claim 2wherein partitioning the film comprises previewing each frame forassignment to one of the clusters.
 10. The method according to claim 1,wherein one of the color constraints defines a black level function. 11.The method according to claim 1, wherein one of the color constraintsdefines a white level function.
 12. The method according to claim 1,wherein one of the color constraints defines a flesh-tone levelfunction.
 13. The method according to claim 1, wherein one of the colorconstraints requires that the average color of the color distribution ofthe cluster is gray.
 14. The method according to claim 13 wherein thelevel of gray is manually settable.
 15. The method of claim 1 furthercomprises specifying color constraints including at least one of colorfidelity, balance, absence of clipping, absence of banding and noiseremoval.
 16. The method of claim 1 further comprising specifying avariable for the one or more color constraints.
 17. The method accordingto claim 1 wherein a color setting is determined for each cluster. 18.The method of claim 1 wherein optimizing the color distributioncomprises adjusting the color settings in each cluster to maximize theentropy among all possible color settings with respect to theconstraints, wherein each color setting is represented as athree-dimensional color histogram.
 19. The method according to claim 1further comprising: iteratively determining a color setting for eachcluster.
 20. The method according to claim 1, wherein the altered colorinformation complies with all of the constraints.
 21. The method ofclaim 1 further comprising: transferring the color information producedby the selected color setting to a digital medium.
 22. The methodaccording to claim 1 further comprising digitizing film frames.
 23. Themethod of claim 21 wherein the digital medium is digital tape.
 24. Themethod of claim 21 wherein the digital medium is a computer disk.
 25. Amethod for automated color control in converting film to digital video,the film being composed of frames containing color information definingone or more scenes the method comprising: converting the film framesinto digital video frames; grouping the digital video frames into one ormore clusters by scene; automatically determining altered colorinformation for each cluster, wherein the altered color informationcomplies with one or more color constraints and the altered colorinformation for the cluster contains substantially the same colorinformation as the film scene.
 26. The method according to claim 25wherein the altered color information for each cluster is optimized suchthat the altered color information shares the maximum color informationwith the film scene subject to compliance with all color constraints.27. The method of claim 25 wherein the specified constraints include atleast one of color fidelity, balance, absence of clipping, absence ofbanding and noise removal.
 28. The method of claim 25 whereindetermining altered color information comprises adjusting color settingsfor a digitization device to maximize the entropy for the color setting.29. The method of claim 28 wherein adjusting the color settingscomprises: calculating the entropy of the altered color information foreach color setting; and selecting the color setting which satisfies theconstraints and maximizes the entropy.
 30. The method of claim 29wherein the color settings comprise at least one of lift, gamma andgain.
 31. The method of claim 28 further comprising: transferring thealtered color information corresponding to the selected color setting toa digital medium.
 32. The method of claim 31 wherein the digital mediumis digital tape.
 33. The method of claim 31 wherein the digital mediumis a computer disk.
 34. A system for automated color control inconverting film to digital video, the system comprising: a digitizationdevice for converting frames of the film into digital video; means forpartitioning the frames into a plurality of clusters, wherein eachcluster includes at least one frame; means for specifying constraintsfor each cluster; and means for optimizing the color information in eachcluster of digital video, wherein the optimized color information is asclose as possible to the color information in the film subject to theconstraints.
 35. The system of claim 34 wherein the constraints compriseat least one of color fidelity, balance, absence of clipping, absence ofbanding and noise removal.
 36. The system of claim 34 wherein the meansfor optimizing adjusts the color settings for each cluster to maximizethe entropy among all possible color settings which respect the colorconstraints.
 37. The system of claim 34 wherein in adjusting the colorsettings the means for optimizing: calculates the entropy for eachpossible color setting complying with the color constraints; and selectsthe color setting which satisfies the constraints and maximizes theentropy.
 38. The system of claim 37 wherein the color settings compriseat least one of lift, gamma and gain.
 39. The system of claim 34 whereinthe digitization device: transfers the color information to a digitalmedium.
 40. The method of claim 39 wherein the digital medium is digitaltape.
 41. The method of claim 39 wherein the digital medium is acomputer disk.
 42. A system for automated color control in convertingfilm to digital video, the system comprising: a digitization device forconverting frames of the film into a digital representation composed ofcolor information; and an optimizer for optimizing the color informationin each cluster of digital video, wherein the optimized colorinformation is as close as possible to the color distribution in thefilm subject to specified constraints.
 43. The system of claim 42wherein the constraints comprise at least one of color fidelity,balance, absence of clipping, absence of banding and noise removal. 44.The system of claim 42 wherein the optimizer adjusts the digitizationdevice according to a color setting for each cluster to maximize theentropy among all possible color settings which comply with theconstraints.
 45. The system of claim 44 wherein in adjusting theoptimizer: calculates the entropy for each color setting; and selectsthe color setting which satisfies the constraints and maximizes theentropy.
 46. The system of claim 45 wherein the color settings compriseat least one of lift, gamma and gain.